Jackle, Annette and Burton, Jonathan and Couper, Mick P (2023) Understanding Society: Minimizing selection biases in data collection using mobile apps. Fiscal Studies, 44 (4). pp. 361-376. DOI https://doi.org/10.1111/1475-5890.12351 (In Press)
Jackle, Annette and Burton, Jonathan and Couper, Mick P (2023) Understanding Society: Minimizing selection biases in data collection using mobile apps. Fiscal Studies, 44 (4). pp. 361-376. DOI https://doi.org/10.1111/1475-5890.12351 (In Press)
Jackle, Annette and Burton, Jonathan and Couper, Mick P (2023) Understanding Society: Minimizing selection biases in data collection using mobile apps. Fiscal Studies, 44 (4). pp. 361-376. DOI https://doi.org/10.1111/1475-5890.12351 (In Press)
Abstract
The UK Household Longitudinal Study: Understanding Society has a programme of research and development that underpins innovations in data collection methods. One of our current focuses is on using mobile applications to collect additional data that supplement data collected in annual interviews. To date, we have used mobile apps to collect data on consumer expenditure, well-being, anthropometrics and cognition. In this article we review the potential barriers to data collection using mobile apps and experimental evidence collected with the Understanding Society Innovation Panel, on what can be done to reduce these barriers.
Item Type: | Article |
---|---|
Uncontrolled Keywords: | UKHLS; panel survey; experiments |
Divisions: | Faculty of Social Sciences Faculty of Social Sciences > Institute for Social and Economic Research |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 20 Jan 2024 12:17 |
Last Modified: | 26 Jan 2024 06:52 |
URI: | http://repository.essex.ac.uk/id/eprint/36841 |
Available files
Filename: Fiscal Studies - 2023 - Jäckle - Understanding Society minimising selection biases in data collection using mobile apps.pdf
Licence: Creative Commons: Attribution 4.0